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Organic/inorganic chemistry, analytical chemistry, electrochemistry, molecular properties, chemical reactions
2,324 datasets
A 504.0 KB dataset containing molecular structure data for a series of non-prostanoid EP4 agonists. Heidi L. Perez published this data in 2026, detailing compounds discovered through high-throughput screening and optimized via structure-activity relationship studies. The dataset includes the lead compound 11a, which was profiled in mouse pharmacokinetic and efficacy models.
A 2026 study by Heidi L. Perez details the discovery and optimization of a novel chemotype of EP4 receptor agonists for treating inflammatory bowel disease. The dataset includes structural data from high-throughput screening and mutagenesis studies, leading to a profiled lead compound. It is published on figshare under a CC-BY-NC-4.0 license.
A 503.9 KB collection of PDB files details the molecular structures of optimized EP4 receptor agonists. Heidi L. Perez authored this dataset, which was last updated in April 2026. It contains computational models and structural data for a novel chemotype discovered through high-throughput screening and SAR studies.
A 504.2 KB dataset from figshare contains structural data related to the discovery of non-prostanoid EP4 agonists for treating inflammatory bowel disease. Heidi L. Perez authored this research, which was last updated in April 2026. It includes computational models and protein structures from high-throughput screening and mutagenesis studies.
Heidi L. Perez published molecular structure data for a series of non-prostanoid EP4 receptor agonists. The dataset includes the optimized lead compound 11a, which was profiled in mouse pharmacokinetic and IBD efficacy studies. The data was last updated in April 2026.
Lead compound 11a demonstrated efficacy in a mouse model of inflammatory bowel disease and induced known hemodynamic changes in systemic circulation. Heidi L. Perez published this dataset on figshare in April 2026, detailing structure-activity relationship studies from a high-throughput screening campaign. The dataset contains chemical and biological data supporting the discovery of a novel agonist chemotype.
Structural and pharmacological data for YYSW001, a highly selective JAK1 inhibitor with an IC50 of 6 nM and >50-fold selectivity over JAK2. It includes results from pharmacokinetic evaluation showing 61.8% oral bioavailability and efficacy data from rat collagen-induced arthritis (CIA) and adjuvant-induced arthritis (AIA) models. The data supports the compound's preclinical development profile.
Comprising structural and pharmacological data for YYSW001, a preferential JAK1 inhibitor with an IC50 of 6 nM and >50-fold selectivity over JAK2. It includes pharmacokinetic data showing 61.8% oral bioavailability and efficacy results from rat collagen-induced arthritis and adjuvant-induced arthritis models. The data is provided in a PDB file format.
Results of MD between key target proteins and active compounds, authored by Guiqin Bai and last updated on April 22, 2026. The dataset is a 5.5 KB XLS file available under a CC-BY-4.0 license on figshare.
NMR data for position-specific 13C/12C analysis of glucose was authored by David W. Hoffman and is hosted by the Texas Data Repository Harvested Dataverse. The dataset was last updated on June 1, 2026.
Dénes Berta's dataset, published on figshare in March 2026, contains computational data for modeling enzyme-catalyzed phosphate hydrolysis. The data supports the Locality Accelerated and Systematically Improvable (LASI) protocol, which combines quantum embedding and local natural orbital methods. It is designed to achieve chemical accuracy at an affordable computational cost for large quantum subsystems.
A dataset supporting the Locality Accelerated and Systematically Improvable (LASI) QM/MM protocol for computational enzymology. It contains results from quantum embedding and DFT calculations, including data for enzyme-catalyzed phosphate hydrolysis reactions. The dataset is provided by author Dénes Berta in an XLS file of 144.0 KB.
A methodological dataset from 2026 detailing an optimized lipid extraction and annotation pipeline for individual chitinous mesozooplankton. The data, authored by Jiwoon Hwang and shared under a CC-BY-4.0 license, supports high-resolution lipidomics to study trophic interactions and carbon cycling in marine ecosystems. The workflow achieved a 2.5-fold increase in lipid recovery and a 4.4-fold gain in signal intensity for single Calanus copepods.
A methodological paper presents an optimized lipid extraction and annotation workflow for marine zooplankton. The protocol yields a 2.5-fold increase in lipid recovery and a 4.4-fold gain in signal intensity from single Calanus copepods. It was developed by Jiwoon Hwang and published in March 2026.
Jiwoon Hwang's 2026 figshare publication details a methodological workflow for lipidomics on individual chitinous mesozooplankton. The protocol achieves a 2.5-fold increase in lipid recovery and a 4.4-fold gain in signal intensity using an optimized Bligh and Dyer extraction with in-line glass bead homogenization. It compares LOBSTAHS and MS-DIAL annotation pipelines and integrates a wax ester-specific fragmentation library.
PDB files contain molecular structures for benzofuran oxoacetic acid compounds synthesized as EPAC1 activators. The dataset, created by David Morgan, includes compounds like DM244, DM357, and DM408 evaluated for binding bias and cellular activity in fibrosis-relevant assays. The total file size is 451.1 KB.
Nemotron-Personas-Korea is a synthetic persona dataset grounded in real-world demographic, geographic, and personality trait distributions of South Korea. It is the first large-scale Korean-language persona dataset, synthesized using attributes such as name, gender, age, marital status, education level, occupation, and residence region based on official statistics from sources including the Korean Statistical Information Service (KOSIS), the Supreme Court, the National Health Insurance Service, the Rural Economic Research Institute, and NAVER Cloud. The dataset is open-source under a CC BY 4.0 license and was created by NVIDIA.
Feifei Chen published this dataset on figshare on 2026-04-27. The data appears to be raw computational chemistry outputs related to the discovery of small molecule inhibitors for pediatric metabolic disorders. The 209.8 MB collection includes files in formats such as FCHK, GJF, TIF, ZIP, MAEGZ, LOG, IN, and GZ.
Liam E. Claton synthesized and characterized a 1275-member library of 24-atom triazine macrocycles for drug discovery research in 2026. The library was created from 50 monomers using a quantitative dimerization process with >99.9% fidelity, validated by liquid chromatography–mass spectrometry. Reactions produced macrocycles, with some monomers exhibiting partial hydrolysis or deprotection.
Geoscience Australia Data published a study on March 25, 2026, combining two-dimensional gas chromatography and compound-specific isotope analysis. The research analyzes diamondoids, n-alkanes, and aromatic hydrocarbons to identify multiple hydrocarbon sources in Australia's offshore Browse Basin. It focuses on distinguishing contributions from non-biodegraded and biodegraded oil fields.